Orchestration and Staging: Fairground: Thrill Laboratory

  • Stuart Reeves
Part of the Human-Computer Interaction Series book series (HCIS)


This chapter describes and analyses Fairground: Thrill Laboratory, a series of evening presentation and performance events that extended a participant’s experience of the fairground ride to a watching audience. This was achieved by streaming in real-time a given rider’s telemetry data (such as accelerometer and heart rate data), derived from biosensing equipment attached to the rider. Audience members, hosted by actors, were picked via a ‘lottery’ to be equipped and participate by riding whilst the remaining audience watched a projected visualisation of the rider’s various data streams, including a video stream of their face and audio from a microphone. In addition to revisiting the roles of audience, participants and actors, and audience-participant transitions, the highlight in this chapter is the work of the orchestrators, a key component in the smooth running of this public event. Orchestrators collaborate with actors to weave together a performance from distributed and disparate elements, with orchestrators managing and intervening in crisis situations, and dealing with technological breakdown. Orchestration opens out the discussion to consider some key subdivisions of the public setting, such as behind-the-scenes, where the telemetry equipment management takes place, and the centre-stage, where actors construct the event’s general atmosphere and make legible the riders’ experience for audience. Finally, orchestration is also considered in terms of the participants’ experience through discussing audience-participant transition, and the ways in which such transition is achieved through a sequence of activities such as the lottery, moving the participant behind-the-scenes, and donning equipment.


Control Area Video Transmitter Audience Member Telemetry Data Ride Operator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag London Limited 2011

Authors and Affiliations

  1. 1.Horizon Digital Economy ResearchUniversity of NottinghamNottinghamUK

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